The 01 loss is known to be more robust to outliers than convex loss models [1]}, [2]}, [3]}. In addition to being robust to outliers the 01 loss is also robust to noise in the training data [4]}, [5]}. Under this loss minimizing the empirical risk amounts to minimizing the empirical adversarial risk [6]}, [7]} with certain assumptions of noise. Convex losses also fail to minimize the adversarial 01 loss on linear models [8]}.
